2013Unpublished venueRequires access

Cascading Defaults and Systemic Risk of a Banking System

Jin‐Chuan Duan, Changhao Zhang

Open publisher page 0 citations

Abstract

Systemic risk of a banking system arises from cascading defaults due to interbank linkages. Any large negative external shock can in principle trigger cascading defaults, but shocks to systematic risk factors, as opposed to banks ' idiosyncratic elements, are more likely to drive cascading defaults and hence to cause higher systemic risk. This paper proposes a structural model for a banking system in which bank assets are subject to both systematic and idiosyncratic risks and bank liabilities contain interbank exposures which may or may not be subject to netting. This model allows us to dene two useful measures: systemic exposure and systemic fragility. The former characterizes the expected losses due to interbank linkages under some prescribed macro stress scenario, whereas the latter measures the pervasiveness of bank defaults under the same condition. In addition, we are able to compute marginal systemic risk measures and use them to rank banks according to their individual contributions to systemic risk. Our model is conducive to examining potential impacts on systemic risk under different banking network configurations. We devise a novel bridge sampling technique specifically for computing these two systemic risk measures, and obtain data and estimates for a network of 15 British banks. Our results are

About this research paper

What this paper is about

Systemic risk of a banking system arises from cascading defaults due to interbank linkages. Any large negative external shock can in principle trigger cascading defaults, but shocks to systematic risk factors, as opposed to banks ' idiosyncratic elements, are more likely to drive cascading defaults and hence to cause higher systemic risk. This paper proposes a structural model for a banking system in which bank assets are subject to both systematic and idiosyncratic risks and bank liabilities contain interbank exposures which may or may not be subject to netting. This model allows us to dene two useful measures: systemic exposure and systemic fragility. The former characterizes the expected losses due to interbank linkages under some prescribed macro stress scenario, whereas the latter measures the pervasiveness of bank defaults under the same condition. In addition, we are able to compute marginal systemic risk measures and use them to rank banks according to their individual contributions to systemic risk. Our model is conducive to examining potential impacts on systemic risk under different banking network configurations. We devise a novel bridge sampling technique specifically for computing these two systemic risk measures, and obtain data and estimates for a network of 15 British banks. Our results are

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Systemic risk of a banking system arises from cascading defaults due to interbank linkages. Any large negative external shock can in principle trigger cascading defaults, but shocks to systematic risk factors, as opposed to banks ' idiosyncratic elements, are more likely to drive cascading defaults and hence to cause higher systemic risk. This paper proposes a structural model for a banking system in which bank assets are subject to both systematic and idiosyncratic risks and bank liabilities contain interbank exposures which may or may not be subject to netting. This model allows us to dene two useful measures: systemic exposure and systemic fragility. The former characterizes the expected losses due to interbank linkages under some prescribed macro stress scenario, whereas the latter measures the pervasiveness of bank defaults under the same condition. In addition, we are able to compute marginal systemic risk measures and use them to rank banks according to their individual contributions to systemic risk. Our model is conducive to examining potential impacts on systemic risk under different banking network configurations. We devise a novel bridge sampling technique specifically for computing these two systemic risk measures, and obtain data and estimates for a network of 15 British banks. Our results are

Key concepts: Systemic risk, Default, Business, Systematic risk, Shock (circulatory), Cascading failure, Credit risk, Financial system

Related papers

Back to paper searchBrowse research topicsOriginal source
Cascading Defaults and Systemic Risk of a Banking System — Research Paper | ScholarLens